Colin Mansfield, Allheartz - AI-Powered Injury & Recovery Assessment | LSI USA '24

Colin Mansfield  0:04  
I'm Colin Mansfield. I'm an orthopedic sports surgeon here in California. I'm also the founder and CEO of all hearts and more our product is focused is outside of the hospital, in the community, and in the home and what we're looking to do as high volume prevention and remote care. And what we're bringing to market is a new kind of computer vision, where we can transform a personal smartphone into a medical sensor that is integrated, portable and autonomous. It's been a major challenge, looking at how we can do a better job at digitizing human motion, which is so important to musculoskeletal medicine. And just as importantly, how do we then integrate this appropriately into our health care systems, we're looking to do this in three major arenas and the community in the clinic and moving to the world of athletics, as well. So we can do a better job at empowering homecare decreasing costs, as well as generating new lines of revenue. And we're gonna be doing this with prevention and remote therapeutic monitoring. And what we provide is both the tool as well as the integrated smart platform to get this done. And much like the advent of the blood pressure cuff empowered new ways of treating cardiovascular health. Well, we are creating as a unifying technology that can cross boundaries, not only across health systems, but also into the world of athletics and into the community. And in doing so what we're really building upon is something we've been trying to do for decades, which is the creation of a new vital sign in musculoskeletal skeletal medicine, which we call mobility. And activity, of course, is the highest prevalent field as the number one payer market and your 6% of the US GDP. And when we look at who was coming into clinics, who was coming into our hospitals, more than one and two, are coming in with musculoskeletal conditions. And so the umbrella this market is quite large, in particular, when we start looking at lost productivity, but where we are focused is in the outpatient ambulatory setting, which is a $20 billion opportunity. And what we are looking to address is a system has not changed much since the time of Hippocrates. And I think we're all quite familiar with this care delivery model. Where you have a problem, you come into a physical location, you see a specialist, and that specialist is going to take you through a very guided evaluation because what we're trying to elicit is the data points of motion and stress in a particular area of your body. In most cases, we then take that information and type it into a chart in rich text format, which is rarely tracked, and done at few time points. And so it's been very difficult to understand how to improve upon this system, both to spend less time in the office to get to the problem before it becomes a problem. And doing this remotely. And this is the technical barrier that we are jumping with our device to combine the targeted nature of an in person evaluation to approach the accuracy of what a gait analysis lab may provide. Not even wearables, no manufacturing and doing this remotely and only necessitating a typical smartphone. We use proprietary neural network systems to take two dimensional video, and then do a three dimensional analysis with this, where we can then bring this into our systems to digitize and integrate. A mobile application connects the user to our AI cloud processor. And we can then take them through a guided evaluation to get the specific motion necessary. And with this, we can then garner the information and bring the actionable data back to the clinic for remote therapeutic monitoring. This is supported in the literature. And we were quite fortunate The Centers for Medicaid and Medicare in 2022 enacted four new CPT codes. So we can have a path to success specifically for musculoskeletal monitoring for a billable device. As we all know, it is notoriously difficult to protect the IP in AI and software. But we're very confident in the data moat that we have provided provided around this project, both with our machine learning models, as well as with the particular data that we're bringing in. We operate on a subscription and monthly active user basis, which is very attractive to clinics as there's no large capital purchase necessary. When our product is being used by patients they can build and we can build when they don't We don't and this has given us very favorable financial projections into 2027. We are employing this in two major divisions on the athletic side and on the clinical side on the athletic side, what we are using this as a screening tool for injury prevention, and on the clinical side for recovery, tracking how this looks on the athletic side and this is one of our trainers working with an athlete and within about 30 seconds and three separate jumps. Our product is able to screen and pick out the appropriate risk factors. So these are high risk factors and they are modifiable, which means that we can screen track and prevent with this product on the clinical side in a similar fashion. We can target specific areas of the body so we can bring the information to the clinician that is necessary. What's wonderful about this is is implant agnostic, and can really improve the journey of patients and clinicians alike, and bring in new outcome measures for tracking. And what's very important about this is that it has custom clinical input, so that we can real time track what is going on in the community, find those who are getting into trouble early, and work on our injury reduction, our readmission, as well as our prevention algorithms. And of course, this is done in a compliance and protected fashion, many avenues of benefit both with cost reduction as well as revenue capture, but this is a smart, scalable and flexible system. And so as traction improves as data comes in our machine learning models are also improving with it. And so this product is always getting better. As we're using it. I painstakingly made this as a clinician myself to fit within clinical workflows, so that we can do a better job at integration a better job and automation without overburdening our clinicians. And this is done without manufacturing, there's no sensors, it's incredibly scalable. So we can really impact equity access, do better at home care. And it's so critical to have this information to improve our value care models. We're now three years into r&d and in 2020 To begin using our pilot product, we're very excited now after a year and a half of use with high risk division one sports athletes, we are showing a 70% injury reduction, which is fantastic. We're very excited about this and we have an IRB submitted. We're now working on further pilot projects with high level D one, all the way down to our 1112 13 year old clubs sports players where we can make huge longitudinal differences. As we move forward with a national prevention campaign. We just finished a large machine learning upgrade as well as improving our integration. Looking forward to later this year. We have four pilot spots chosen for our clinical launch, and this will be in New York, Pennsylvania and New Jersey. We're also very confident in our risk mitigation coming out as a class one discretionary exemption device, so that we can move forward with higher volume research, expand our r&d, and we're currently in a seed round to raise to get to these next steps. We have a fantastic team myself, I'm both a surgeon as well as a coder. In fact, the first algorithm this company is based upon I wrote myself, I think has given me some unique insight both into the vision but also the potential of this product. I'm very happy working with Joe who is also a co development group and a lot of experience in successful private projects. Frauds is with us advising on strategy and operation. He also has incredible experience in the field and to product companies himself. Scott recently joined us to help lead up our sales and marketing and we have a tremendous business advisor and very talented development group. And so I think with this tool, we can really offer better ways for our health systems to help the community but also get into help with our athletes and our teams. So we can accelerate the way that we can deliver musculoskeletal medicine remotely. I thank you for your time.